When providing video or image services, service providers may want to monitor the subjective quality of their users' experience, which may be commonly referred to as the Quality of Experience (QoE) score or Motion Opinion Score (MOS). Due to the complex nature of the human visual system (HVS), QoE scores may be affected by both the content of the video media as well as the quality of video signal. Specifically, human perception may be more sensitive to qualitative differences for certain classes of content than other classes of content. For instance, distortion may be more noticeable during periods of light motion than during periods of heavy motion (e.g., action scenes). Additionally, the HVS may be more sensitive to some luma (or brightness) levels, and consequently the average luma level of a frame or sequence of frames may impact the QoE score. As a result, monitoring traditional Quality of Service (QoS) metrics (e.g., bit error rate, etc.) alone may be an unreliable means for gauging QoE.
One technique for accurately gauging QoE scores is to obtain subjective assessments of image quality based on real-time human response, a procedure for which is outlined in the International Telecommunications Union (ITU) Radiocommunication Sector (ITU-R) recommendation BT.500 entitled “Methodology for Subjective Assessment of Quality of Television Pictures.” Although accurate, subjective testing of this nature may require strict ‘laboratory type’ settings, and therefore may be expensive, time-consuming, and altogether impractical. As such, an objective approach for accurately gauging QoE is desired.